Darryl J. Downing

GlaxoSmithKline (United States)

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James S. Bogard

Oak Ridge National Laboratory

James Turner

University of Birmingham

D.H. Pike

Oak Ridge National Laboratory

David Pack

Longwood University

James Turner

Oak Ridge National Laboratory

W.F. Lawkins

Oak Ridge National Laboratory

Valerii V. Fedorov

GlaxoSmithKline (United States)

S. B. McLaughlin

Oak Ridge National Laboratory

George Ostrouchov

Oak Ridge National Laboratory

Michael R. Chernick

Lankenau Institute for Medical Research

Cooperative Institutions

Oak Ridge National Laboratory

University of Tennessee at Knoxville

Office of Scientific and Technical Information

United States Department of Energy

Martin Marietta Materials (United States)

Lockheed Martin (United States)

National Technical Information Service

University of Florida

New York State Department of Agriculture and Markets

Cornell University

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NLO error propagation exercise: statistical results

David Pack Darryl J. Downing

Error propagation is the extrapolation and cumulation of uncertainty (variance) above total amounts of special nuclear material, for example, uranium or /sup 235/U, that are present in a defined location at a given time. The uncertainty results from the inevitable inexactness of individual measurements of weight, uranium concentration, /sup 235/U enrichment, etc. The extrapolated and cumulated uncertainty leads directly to quantified limits of error on inventory differences (LEIDs) for such material. The NLO error propagation exercise was planned as a field demonstration of the utilization of statistical error propagation methodology at the Feed Materials Production Center in Fernald, Ohio from April 1 to July 1, 1983 in a single material balance area formed specially for the exercise. Major elements of the error propagation methodology were: variance approximation by Taylor Series expansion; variance cumulation by uncorrelated primary error sources as suggested by Jaech; random effects ANOVA model estimation of variance effects (systematic error); provision for inclusion of process variance in addition to measurement variance; and exclusion of static material. The methodology was applied to material balance area transactions from the indicated time period through a FORTRAN computer code developed specifically for this purpose on the NLO HP-3000 computer. This paper contains a complete description of the error propagation methodology and a full summary of the numerical results of applying the methodlogy in the field demonstration. The error propagation LEIDs did encompass the actual uranium and /sup 235/U inventory differences. Further, one can see that error propagation actually provides guidance for reducing inventory differences and LEIDs in future time periods.

Propagation of uncertainty

Fortran

10.2172/5053984

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Univariate Tests for Time Series Models

Technometrics (1995)

Darryl J. Downing Jeff B.Cromwell Walter C. Labys Michel Terraza

Introduction Testing for Stationarity Testing for Normality Testing for Independence Testing for Linear or Nonlinear Dependence Linear Model Specification Nonlinear Model Specification Testing for Model Order Testing for Residual Process Computational Methods for Performing the Tests

Univariate

Univariate analysis

10.2307/1269923

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Nutrient risk assessment in a decision theoretic context

Journal of Nutritional & Environmental Medicine (2008)

Shireen Hickey Darryl J. Downing Robert H. J. Verkerk A. Osbourne Len Noriega

Background. This study describes a decision‐theoretic approach to nutrient assessment based on Bayesian methods, which can be used to give accurate estimates of optimum intakes. Analysis of risk is an incomplete technique for dealing with nutrients and other substances that, by definition, have an associated benefit.Results. This paper shows that the risk analysis methods being developed by the Codex Commission on Nutrition and European Food Safety Authority, among others, are inappropriate for assessing safe nutrient intake levels. Decision theoretic methods incorporate benefits associated with these essential nutrients, as well as potential risk. Conclusion. These methods allow for missing or incomplete data, which conventional risk analysis does not.

European commission

10.1080/13590840802305407

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Water resources evaluation. [Use of intervention and transfer function analyses in modeling effects of a dam and rainfall quantities on the flow rate of a river]

Darryl J. Downing G.W. Westley David Pack

Weekly river flow data is analyzed using the techniques of Box and Jenkins. Intervention analysis, first proposed by Box and Tiao, is applied where the intervening event is the creation of a dam. The idea of intervention analysis is combined with transfer function analysis to utilize rainfall data in a unique way and greatly improve the predictive ability of the model, as well as giving meaningful physical interpretations to the parameters in the model.

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Interactive effects of ambient ozone and climate measured on growth of mature loblolly pine trees

Canadian Journal of Forest Research (1996)

S. B. McLaughlin Darryl J. Downing

Seasonal growth patterns of mature loblolly pine (Pinustaeda L.) trees over the interval 1988–1993 have been analyzed to evaluate the effects of ambient ozone on growth of large forest trees. Patterns of stem expansion and contraction of 34 trees were examined using serial measurements with sensitive dendrometer band systems. Study sites, located in eastern Tennessee, varied significantly in soil moisture, soil fertility, and stand density. Levels of ozone, rainfall, and temperature varied widely over the 6-year study interval. Regression analysis identified statistically significant influences of ozone on stem growth patterns, with responses differing widely among trees and across years. Ozone interacted with both soil moisture stress and high temperatures, explaining 63% of the high frequency, climatic variance in stem expansion identified by stepwise regression of the 5-year data set. Observed responses to ozone were rapid, typically occurring within 1–3 days of exposure to ozone at ≥40 ppb and were significantly amplified by low soil moisture and high air temperatures. Both short-term responses, apparently tied to ozone-induced increases in whole-tree water stress, and longer term cumulative responses were identified. These data indicate that relatively low levels of ambient ozone can significantly reduce growth of mature forest trees and that interactions between ambient ozone and climate are likely to be important modifiers of future forest growth and function. Additional studies of mechanisms of short-term response and interspecies comparisons are clearly needed.

Loblolly pine

10.1139/x26-077

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Citations (44)

FORAST Database

Carbon Dioxide Information Analysis Center (CDIAC) Datasets (1995)

S. B. McLaughlin Darryl J. Downing T. J. Blasing Barbara L. Jackson David Pack

10.3334/cdiac/vrc.db1005

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COMPARISON OF REGRESSION AND TIME‐SERIES METHODS FOR SYNTHESIZING MISSING STREAMFLOW RECORDS¹

JAWRA Journal of the American Water Resources Association (1989)

John J. Beauchamp Darryl J. Downing Steven F. Railsback

ABSTRACT: Regression and time‐series techniques have been used to synthesize and predict the stream flow at the Foresta Bridge gage from information at the upstream Pohono Bridge gage on the Merced River near Yosemite National Park. Using the available data from two time periods (calendar year 1979 and water year 1986), we evaluated the two techniques in their ability to model the variation in the observed flows and in their ability to predict stream flow at the Foresta Bridge gage for the 1979 time period with data from the 1986 time period. Both techniques produced reasonably good estimates and forecasts of the flow at the downstream gage. However, the regression model was found to have a significant amount of autocorrelation in the residuals, which the time‐series model was able to eliminate. The time‐series technique presented can be of great assistance in arriving at reasonable estimates of flow in data sets that have large missing portions of data.

10.1111/j.1752-1688.1989.tb05410.x

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Measuring Radioactivity

James Turner Darryl J. Downing James S. Bogard

This chapter contains sections titled: Introduction Normal Approximation to the Poisson Distribution Assessment of Sample Activity by Counting Assessment of Uncertainty in Activity Optimum Partitioning of Counting Times Short-Lived Radionuclides Problems

Sample (material)

10.1002/9783527646548.ch9

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Statistical Performance Measures

James Turner Darryl J. Downing James S. Bogard

This chapter contains sections titled: Statistical Decisions Screening Samples for Radioactivity Minimum Significant Measured Activity Minimum Detectable True Activity Hypothesis Testing Criteria for Radiobioassay, HPS N13.30-1996 Thermoluminescence Dosimetry Neyman–Pearson Lemma Treating Outliers – Chauvenet's Criterion Problems

Lemma (botany)

Statistical Analysis

10.1002/9783527646548.ch10

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Technique for detecting a small magnitude loss of special nuclear material

D.H. Pike Michael R. Chernick Darryl J. Downing

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